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LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2024, 10(3), pp.57-64
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : May 15, 2024
  • Accepted : June 10, 2024
  • Published : June 30, 2024

Hyeok-Don Kwon 1 Kwon Jung-Hyok 1 SOLBEE LEE 1 EUIJIK KIM 1

1한림대학교

Accredited

ABSTRACT

In this paper, we propose a Line-of-Sight (LoS)/Non-Line-of-Sight (NLoS) identification- based Human Activity Recognition (HAR) system using Channel State Information (CSI) to improve the accuracy of HAR, which dynamically changes depending on the reception environment. to consider the reception environment of HAR system, the proposed system includes three operational phases: Preprocessing phase, Classification phase, and Activity recognition phase. In the preprocessing phase, amplitude is extracted from CSI raw data, and noise in the extracted amplitude is removed. In the Classification phase, the reception environment is categorized into LoS and NLoS. Then, based on the categorized reception environment, the HAR model is determined based on the result of the reception environment categorization. Finally, in the activity recognition phase, human actions are classified into sitting, walking, standing, and absent using the determined HAR model. To demonstrate the superiority of the proposed system, an experimental implementation was performed and the accuracy of the proposed system was compared with that of the existing HAR system. The results showed that the proposed system achieved 16.25% higher accuracy than the existing system

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